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Prosiding Seminar Nasional Official Statistics
Published by Politeknik Statistika STIS
ISSN : 27721970     EISSN : 27721970     DOI : https://doi.org/10.34123/semnasoffstat.v2022i1
Core Subject : Economy, Humanities, Science, Social,
Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences
prosiding seminar ini bertujuan untuk menghasilkan berbagai pemikiran solutif, inovatif, dan adaptif terkait isu, strategi, dan metode yang memanfaatkan official statistics
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 729 Documents
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Perbandingan Agglomerative Nesting dan K-Means untuk Klasterisasi Ketimpangan Gender berdasarkan Dimensi Kesehatan Reproduksi Raihannabil, Syfriza Davies; Ilyas, Hilmi Malika Atim; Shafira, Hervira Nur; Riani, May Alya; Hastin, Nadya Noor; Siregar, Tiara Khorijah Hamid
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.1977

Abstract

Gender inequality in Indonesia is ranked 4th out of 11 ASEAN countries with key problems such as high maternal mortality rates and teenage births. Indonesia ranks 3rd with the highest maternal mortality rate in Southeast Asia. Besides that, around 61% of provinces still have adolescent birth rates above the national average. This research uses clustering techniques to group provinces based on reproductive health dimensions to provide insight for policymakers. The two clustering methods used are Agglomerative Nesting (AGNES) and K-Means. The analysis found that the K-Means method was more effective in producing three clusters: 15 provinces in the medium category, 10 provinces in the high category, and 9 provinces in the low category. It is hoped that the results of this research can help the government make appropriate policies regarding improvements in the reproductive health dimensions to achieve gender equality in Indonesia, especially in provinces with high categories.
Analisis Spasial Pengaruh Faktor Sosial dan Lingkungan terhadap Prevalensi Hipertensi Zen, Rizqi Annisa; Pramana, Setia
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.1979

Abstract

Hypertension is one of the most common cardiovascular diseases suffered by people in the world. In Indonesia, around 34.1 percent of the population aged 18 years and over suffers from hypertension. Factors that cause hypertension are always associated with genetic and lifestyle factors, even though environmental and social factors also contribute to the occurrence of hypertension. This research was conducted to identify the influence of social and environmental factors on hypertension. The data used comes from Basic Health Research (Riskesdas) in 2018, publications by the Central Statistics Agency (BPS), as well as satellite image data. Satellite imagery is able to provide an accurate and up to date picture of air quality, surface temperature and vegetation distribution. The research was carried out with a spatial approach using the Spatial Autoregressive Model (SAR) method. The results of the analysis show that the lag parameter has a significant effect on the prevalence of hypertension. Meanwhile, the only variable that has a significant influence is Land Surface Temperature (LST), while the variables are GRDP per capita, RLS, TPT, Nitrogen Dioxide (NO2), Carbon Monoxide (CO), Sulfur Dioxide (SO2), and Normalized Difference Vegetation Index (NDVI) has no significant effect on the prevalence of hypertension.
Pendugaan Area Kecil untuk Persentase Balita Miskin Tingkat Kabupaten/Kota di Provinsi Papua Tahun 2023 Menggunakan Pendekatan EBLUP dengan Informasi Klaster Fusur, Alma Rohmah; Ubaidillah, Azka
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.1981

Abstract

The development of a country depends on the quality of its human resources. In 2020, Indonesia's Human Capital Index (HCI) is 0.54. This figure is relatively low compared to other Southeast Asian countries. One of the causes of Indonesia's low HCI rate is poverty. In 2022, the highest percentage of poor children is in Papua. In addition, under-five are the highest poor group among other age groups. Direct estimation often results in less precise guesses due to insufficient sample size. Even direct estimation cannot estimated when an area has no sample. This study uses SAE EBLUP method with cluster information to get the estimated percentage of under-five poverty. The results show that 7 districts/cities in Papua Province have a direct estimator RSE of more than 25%. Using cluster analysis, direct estimators with RSE for unsampled areas were produced, and EBLUP estimators with cluster information were proven to be better than direct estimators from the RSE produced lower than the direct estimator RSE.
Pendugaan Area Kecil Tingkat Pengangguran Terbuka Level Kecamatan Di Provinsi Kepulauan Riau Tahun 2022 Puspita, Desak Nyoman Febrina Ambara; Ubaidillah, Azka
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.1982

Abstract

Kepulauan Riau is the province with the second highest Unemployment Rate (TPT) in 2022. Kepulauan Riau’s TPT has doubled In last decade. It was 5,08 percent in August 2012 to 10,34 percent in August 2020. Kepulauan Riau has 31,8 percent of desperate unemployment. Unemployment alleviation policy is more efficient if it is focused on sub-districts area. However, TPT is available up to district level. Sakernas August 2022 does not have sufficient sample size to estimate TPT in the sub-district level. Therefore, this study aims to estimate TPT at sub-district level in Kepulauan Riau in 2022 using Small Area Estimation (SAE) with additional information from the Potensi Desa 2021. The results showed that Hierarchical Bayes Beta SAE produced sub-district TPT estimators with smaller relative standard errors than direct estimation. Sub-districts with high TPT values in Kepulauan Riau are spread in urban areas so that they require special policies in reducing unemployment.
Pengaruh Perubahan Pendapatan dan Biaya Telekomunikasi Terhadap Konsumsi Rumah Tangga Indonesia Indrawati, Riannie
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.1991

Abstract

This study aims to determine the effect of changes in income and telecommunication expenditure on Indonesian household consumption using Susenas data for 2019. The household expenditure structure was analyzed using the AIDS model and SUR estimation. The estimation results show the income elasticity of telecommunication in 2019 is 1,2923 which indicates that telecommunications are luxury goods that are elastic to changes in income. The own-price elasticity for telecommunication is -0,5510 so that telecommunications are price inelastic.
Peramalan Produksi Beras Indonesia Tahun 2024: Pemenuhan Target Produksi Beras Nasional dan Upaya Mencapai Kemandirian Pangan Putri, Aida Devanty; Haya, Aqilla; Crisanty, Tengku Mashitah
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.1994

Abstract

To ensure food independence, achieving production sufficiency is essential. The government has targeted rice as the primary commodity for self-sufficiency. This study aims to estimate rice production up to December 2024 to evaluate Indonesia’s potential in achieving food independence through the 2024 rice production target. Utilizing rice production data from 2019 to April 2024 provided by BPS-Statistics Indonesia, the study employs SARIMA model (2,0,0)(0,1,1)12. The findings suggest that rice production in Indonesia is projected to reach only approxiamtely two-thirds of the national production target for 2024, and indicating a decreased in rice compared to 2023. The literature review underscores the need for strategies such as increasing the availability of land rice cultivation, diversifying food source to reduce dependence on rice, and the implementing technological innovations and information systems to enhance food diversity.
Perbandingan Algoritma dan Pemetaan Total Suspended Solid di Kawasan Pesisir Indonesia Berdasarkan Data Penginderaan Jauh Berbasis Google Earth Engine Latifa, Afina; Marsisno, Waris
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.1999

Abstract

Indonesia's waters are threatened by marine pollution from various sources, which harms marine ecosystems and human health. Total Suspended Solids (TSS) is a key parameter indicating marine pollution. This study aims to identify the MNDWI threshold value for coastal mapping in Indonesia using remote sensing data, compare TSS calculation algorithms to obtain the most accurate TSS estimates, and map TSS concentrations in Indonesia's coastal areas based on the best TSS algorithm. The collected remote sensing data were analyzed using Normalized Mean Absolute Error (NMAE), Root Mean Square Error (RMSE), and mapping techniques. The research mapped Indonesia's coastal areas with a Modified Normalized Difference Water Index (MNDWI) threshold value ≥ 0.06. The Laili algorithm was found to be the most accurate for TSS calculation, with an NMAE of 2.31% and an RMSE of 20.44. Additionally, TSS concentrations in Indonesia's coastal areas were mapped using the Laili, Liu, and Wijaya algorithms.
Strategi Menjaga Ketahanan Industri Furnitur Jawa Tengah di Era Digitalisasi Amelia, Reni; Mun'im, Akhmad
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2000

Abstract

The era of the 4.0 industrial revolution is driving digitalization in the furniture industry, including the expansion of marketing through the internet. This study examines the impact of digitalization on the income of furniture industry entrepreneurs and the characteristics of those who adopt it in Central Java, using data from the National Labor Force Survey in August 2022. The results of the t-Student test show that entrepreneurs who utilize digitalization have higher average incomes. An association test also indicates a link between digitalization and income. The results of random undersampling and oversampling classification and regression trees identify two characteristics of furniture industry entrepreneurs who utilize digitalization: those who work with the help of permanent/paid workers, or work alone, or with the help of non-permanent/unpaid workers, and those from the Pre Boomers, Millennials, or Z generations. The proposed strategies to maintain the resilience of the furniture industry in Central Java in the digital era include improving digital literacy among entrepreneurs, especially for older individuals or those with limited access to technology.
Variabel-Variabel yang Memengaruhi Kualitas Pembangunan Manusia Kabupaten/Kota di Provinsi Maluku Utara Tahun 2015-2022 Saputra, Martino Dwi; Budyanra, Budyanra
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2011

Abstract

Based on the preamble of the 1945 Constitution, the national goals of Indonesia are to promote the general welfare and to educate the nation's life. This can be seen through the quality of human development. Despite North Maluku Province having an economic growth rate consistently above the national average and a poverty rate consistently below the national average from 2015 to 2022, its human development quality remains below the national level, which is contradictory. This study aims to analyze the variables that influence the quality of human development in the regencies/cities of North Maluku Province from 2015 to 2022. The method used is panel data regression analysis. The results of the study show that internet access, electricity access, and access to proper sanitation positively impact the quality of human development, while the Open Unemployment Rate negatively impacts the quality of human development in the regencies/cities of North Maluku Province from 2015 to 2022. To improve the quality of human development, the government can implement appropriate policies targeting the factors that influence human development quality.
Perbandingan Metode Varmax Dan Prophet Dalam Peramalan Dan Analisis Harga Optimal Umroh Di Indonesia Daziga, Ichwanda Brilliana; Gunardi, Gunardi
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2016

Abstract

The optimal Umrah package price for organizers and consumers is a question. So far, determining package prices based on the facilities offered by the organizers has been done by calculating manually. For consumers to see the best price with the best facilities, of course they need benchmarks. This research aims to predict the price of Umrah packages using the Vector Autoregressive Moving Average With Exogenous Variables (VARMAX) statistical method compared with the Prophet method. Apart from endogenous factors, external variables are also added, namely the exchange rate. After that, the best model with the smallest values of Mean Absolute Error (MAE), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE) is selected. It was found that the best model for predicting prices was the VARMAX (2,1) model with MAE, MAPE and MSE values of 2.2896, 7.5395 and 7.7435 respectively. It is hoped that the analysis of the results of forecasting prices for Umrah packages in Indonesia can be taken into consideration by both parties, namely Umrah organizers and consumers.

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